Applications and practices
Bring enterprise expertise into AI development across customer, professional, and operational work.
Explore how Teammately’s agents elicit the judgment a task requires, engineer the coverage that represents it, and guide improvements to harnesses and weights. Start with a development practice or the industry context closest to your work.
Engineering practices
These practices examine three distinct development objectives. Each connects expert participation and benchmark representation to the candidate behavior your team needs to improve.
Make a coding-agent skill useful beyond the tasks that inspired it. Test invocation, judgment, verification, and behavior on unfamiliar repositories.
Read the practice Operational agentsTest decisions through tools and changing state. Construct the dependencies, partial results, and recovery conditions a static prompt cannot exercise.
Read the practice Model developmentDirect training-data augmentation toward a missing distinction. Connect expert judgment and coverage to an improvement assessed on separate cases.
Read the practiceIndustry studies
A workable rebooking, a supported conclusion, and a useful diagnostic step require different expertise. These studies examine the decisions, coverage, and improvement opportunities in each application, with links to the engineering practices behind them.
These are applied studies of development and assessment, not reports of customer deployments or measured outcomes.
Product relevance leaves the tradeoff unresolved. Establish which attributes, compromises, and alternatives fit the customer’s actual need.
Read the study Airlines · Customer supportAn available seat is only part of a workable recovery. Test support decisions across journey dependencies, passenger needs, and changing booking state.
Read the study Financial Services · Research and draftingAccurate facts can still support an unjustified conclusion. Assess source interpretation, missing context, and the boundary of the intended communication.
Read the study Enterprise SaaS · Technical supportThe same symptom can require different resolutions. Test diagnosis against the customer’s configuration, permissions, and evidence of what happened.
Read the study Healthcare · Documentation supportA summary can be accurate sentence by sentence and still change the record’s meaning. Test material omissions, chronology, and uncertainty for the intended review.
Read the study Insurance · Claims assistanceSimilar claim narratives can require different interpretations. Make policy applicability, evidence gaps, and decision status part of the assessment.
Read the study Logistics · Exception managementA faster recovery on one leg can fail elsewhere in the network. Connect diagnosis, executable alternatives, and customer commitments to the available evidence.
Read the study Industrial · Maintenance assistanceLocal modifications and operating conditions can change whether a familiar procedure applies. Turn that knowledge into criteria for a justified next step.
Read the study Automotive · Diagnostic assistanceA matching symptom does not establish an applicable procedure. Test whether the next diagnostic step follows from this vehicle, its history, and the available evidence.
Read the study Telecommunications · Service troubleshootingThe next useful step depends on incident evidence, service configuration, and checks already completed. Test diagnosis that can move beyond a standard script.
Read the study Travel · Planning and bookingIndividually appealing options can form an impractical trip. Preserve traveler priorities across timing, pacing, availability, and booking conditions.
Read the study Ride sharing & Food delivery · Participant supportA remedy affects people with different accounts and responsibilities. Test evidence handling, justified attribution, and escalation across participant roles.
Read the study Brands · Creative developmentA style guide leaves many creative decisions implicit. Preserve campaign intent, supported claims, and meaningful variation across markets and formats.
Read the studyThe judgment behind the application
Industry is one part of the context. The form of judgment determines what experts need to clarify and what the benchmark should establish. Several of these needs can coexist in the same application.
Shopping, travel planning, and creative work can admit several defensible choices. Experts explain which tradeoff matters, when to clarify, and what would reverse a preference. Rubrics preserve that context so a benchmark can reward useful variation.
Research, claims assistance, and documentation review require judgment about what the available material establishes. Experts identify material omissions, qualifications, and missing conditions. The benchmark can then test those distinctions separately from factual recall.
Passenger recovery, service operations, and software agents depend on tools, changing state, and the consequences of earlier actions. Expert criteria and constructed worlds make those dependencies part of an offline trial.
What makes the work valuable
Expert participation creates value when its findings change what your team can test, teach, or improve. Assess that contribution alongside the work agents undertake to make the expertise usable.
Identify what expert participation clarified and how agents developed it into rubrics, policy boundaries, or coverage. Retain the conditions behind the judgment when applying it to further work.
Make the situations and proportions explicit across ontologies. Examine difficult combinations deliberately, and keep their emphasis visible when interpreting the result.
Compare candidate behavior under defined conditions, including regressions and unresolved cases. Account for expert participation alongside the preparation, engineering, and compute the work required.
Bring one difficult decision, an existing benchmark, or a candidate that keeps failing in a particular context. We can define the expert contribution, coverage, and assessment that would make the next development effort useful.